TIER 01
Assessment
A confidential workflow and infrastructure review. Output: a written architectural recommendation, sizing, isolation posture and a deployment roadmap. Delivered whether or not the engagement continues.
Review assessment scopeSovereign AI infrastructure · regulated organisations
Sovereign AI environments for organisations that cannot route sensitive work through public models.
A boutique practice that designs and deploys private AI infrastructure inside the client perimeter engineered for organisations operating under regulatory, contractual or data-residency constraints. Inference, retrieval and workflow remain under the client's control: auditable, vendor-independent, and aligned with the governance posture the organisation already operates under.
01 · What I do
Four engagement modes, scoped to where the organisation is in its sovereign AI adoption.
TIER 02
Deployment
Turn-key delivery of a sovereign AI environment inside the client perimeter inference, retrieval over the internal corpus, network isolation, and operator handover. Typical timeline: one to two weeks from kick-off to operational use.
Review deployment scopeTIER 03
Operations
Continuous lifecycle management under a defined SLA: model updates, corpus ingestion, monitoring, and governance reporting. A monthly review keeps the environment aligned with how the organisation actually uses it.
Review operations scopeTIER 04
Bespoke
Engagements that extend beyond the assistant internal document pipelines, line-of-business integrations, knowledge-graded interfaces. Fixed scope, fixed price, fixed timeline.
Review bespoke engagements02 · Why a boutique practice
Why a boutique practice rather than a generalist consultancy.
01
Regulated-industry fluency
The practice operates exclusively with organisations under regulatory or contractual sensitivity legal, healthcare, finance, logistics, manufacturing. Questions around privilege, retention, jurisdiction, GDPR Article 28/32 and sector-specific governance are answered directly, without the translation tax of a generalist consultancy.
02
Fixed scope, fixed timeline
Engagements are scoped in writing before they begin. No open-ended hourly billing, no drift. If a requirement falls outside the agreed architecture, the practice surfaces it before the engagement starts.
03
Vendor independence by design
Every environment is built on an open-architecture stack, owned and operated inside the client perimeter. The client retains the ability to operate, modify or transfer the system without dependency on the practice, on a single model provider, or on an external inference platform.
04
Principal-led delivery
Engagements are led end-to-end by the principal, Nikita Chetverikov scoping, architecture, deployment, governance handover. No account layer, no junior delivery. Decisions reach the buyer in hours, not weeks.
03 · Architecture
An open-architecture stack, owned and operated inside your perimeter.
On-premise compute
Inference layer
- - Open-weight foundation models
- - Quantised for on-prem hardware
- - Selection guided by workload and isolation requirements
Document grounding
Retrieval layer
- - Vector index over the internal corpus
- - Permission-aware retrieval
- - Citation back to source documents
Internal automation
Workflow layer
- - Event-driven internal pipelines
- - Integration with line-of-business systems
- - Auditable execution trail
Compliance posture
Isolation perimeter
- - Outbound egress constrained at the firewall
- - Air-gap-capable architecture
- - Audit-ready network policy
Hardware
Compute substrate
- - Low-power inference nodes for constrained-footprint deployments
- - GPU substrates where throughput envelope requires
- - Sized against assessment specification
04 · Reference scenarios
Reference engagements across regulated environments.
REF 001
Law firm
PrivilegeNDA/MSA/DPASLANetwork isolation
Privileged document analysis under client-confidentiality constraints.
A twelve-attorney firm required AI-assisted analysis of NDAs, MSAs, DPAs, engagement letters, motions and discovery materials but could not route client-confidential text through a public model provider without breaching privilege. A sovereign inference environment was deployed inside the firm's perimeter, with retrieval over the document corpus and isolation at the network layer. Attorney-client privilege intact, response-time SLA honoured, drafting and review cycles materially compressed.
Read the full law-firm RAG case study →Users12
Time to deploy5 days
Per-contract review40m → 3m
REF 002
Private clinic
Medical recordsPatient intake interfaceICD-10On-premise
Structured medical records and patient intake without patient data leaving the clinic.
A private clinic required two capabilities: structured transcription of doctor–patient consultations into form-025/u records with ICD-10 coding, and a patient intake interface that captures symptoms and pre-visit context. Both run on infrastructure inside the clinic perimeter; no patient data leaves the building.
See the clinic NER deployment notes →Programs2
Record filling15m → 1m
Booking automation80%
REF 003
Research lab
DPIAGDPRFERPA-alignedAir-gap-capable
Sovereign AI capability for a research lab no student, grant or unpublished data leaving campus.
A university research group required ChatGPT-grade assistance over grant proposals, unpublished datasets and student records. Cloud assistants created a GDPR/FERPA exposure the DPO could not sign off. A sovereign inference environment was deployed inside the campus perimeter in fourteen days, with retrieval over the lab share, network isolation and DPIA-ready audit logging. Zero cloud calls leaving campus.
Read the 14-day research-lab rollout notes →Time to deploy14 days
Users~30 researchers
Cloud calls leaving campus0
Note - reference engagements are described with engagement-permissible detail. Quantitative outcomes vary per environment; figures shown are derived from comparable deployments and the practice's internal benchmarks. Engagement-specific scoping precedes any quantitative commitment. Discuss an engagement.
05 · Process
From first engagement to production environment - typically inside three weeks.
- STEP 0130 min · confidential
Qualification
A confidential review of the organisation, the workflow, and the regulatory posture to confirm whether sovereign AI is the appropriate response.
- STEP 0290 min · scoped
Assessment
Workflow review, infrastructure sizing, architectural recommendation, written roadmap. Credited against the deployment engagement.
- +30 days free supportSTEP 037 working days
Deployment
Provisioning, isolation, document ingestion, knowledge transfer. The environment enters operational use within the same week.
- STEP 04Monthly
Operations
Continuous model lifecycle management, monitoring, and governance reporting under a defined SLA.
06Introductory call
An introductory conversation confidential, thirty minutes.
Describe the organisation, the workflows under consideration, and the constraints sensitive data cannot cross. The reply will be an honest assessment of whether sovereign AI is the appropriate response and, where it is not, a referral to a practice that is better suited.